Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA
Tomer Kaftan

Tomer Kaftan
Graduate Student, University of Washington

Tomer Kaftan is a second-year PhD student at the University of Washington, working with Magdalena Balazinska and Alvin Cheung. His research interests include machine learning systems, distributed systems, and query optimization.  Previously, Tomer was a staff engineer in UC Berkeley’s AMPLab, working on systems for large-scale machine learning. He holds a degree in EECS from UC Berkeley. He is a recipient of an NSF Graduate Research Fellowship.

Sessions

4:20pm–5:00pm Thursday, March 8, 2018
Cuttlefish: Lightweight primitives for online tuning
Big data and data science in the cloud, Data engineering and architecture
 Location: 230 C
Tomer Kaftan (University of Washington)
Tomer Kaftan offers an overview of Cuttlefish, a lightweight framework prototyped in Apache Spark that helps developers adaptively improve the performance of their data processing applications by inserting a few library calls into their code. These calls construct tuning primitives that use reinforcement learning to adaptively modify execution as they observe application performance over time. Read more.